herding

Name	herding JSON
Version	0.0.2 JSON
	download
home_page	https://github.com/microprediction/herding
Summary	Kernel herding
upload_time	2025-02-06 17:32:56
maintainer	None
docs_url	None
author	microprediction
requires_python	None
license	MIT
keywords
VCS
bugtrack_url
requirements	numpy scipy
Travis-CI	No Travis.
coveralls test coverage	No coveralls.

            # herding
Kernel herding is a kind of quasi-monte carlo where samples are chosen successively to approximate known kernel moment constraints. 

In the [video](https://github.com/microprediction/herding/tree/main/docs/assets/video) also linked below, the green dots are landmark locations `y` and the expected value of a gaussian kernel `E[ker(x,y)]` is assumed known for the desired distribution for `x`, which happens to be Gaussian.   

See [examples](https://github.com/microprediction/herding/tree/main/examples)


[![Herding Demo](docs/assets/images/herding_video_thumb.png)](docs/assets/video/herding_video_low_res.mp4)



            

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